结直肠癌术后肠内营养不耐受的影响因素及预测模型构建

顾荣; 沈如婷; 姜露; 杨洋; 叶向红; 黄小鹏

doi:10.16766/j.cnki.issn.1674-4152.004485

结直肠癌术后肠内营养不耐受的影响因素及预测模型构建

doi: 10.16766/j.cnki.issn.1674-4152.004485

东部战区总医院普通外科, 江苏南京 210002

基金项目:

江苏省自然科学基金项目 BK20241676

军事医学创新工程项目 18CXZ040

详细信息

通讯作者:
黄小鹏, E-mail：xp5289h@126.com

中图分类号: R735.3 R459.3
计量
- 文章访问数: 11
- HTML全文浏览量: 4
- PDF下载量: 1
- 被引次数: 0
出版历程
- 收稿日期: 2025-05-13
- 网络出版日期: 2026-10-23

The influencing factors and development of a prediction model for postoperative enteral nutrition intolerance in colorectal cancer

Department of General Surgery, Eastern Theater Command General Hospital, Nanjing, Jiangsu 210002, China

摘要

摘要: 目的构建结直肠癌术后肠内营养不耐受发生风险的预测列线图模型，并对该模型的预测效能进行初步验证。方法回顾性选取2021年1月—2024年6月在东部战区总医院行手术治疗的185例结直肠癌患者作为研究对象，患者术后均给予肠内营养支持，根据患者是否出现不耐受症状，分为耐受组（129例）和不耐受组（56例）。收集2组患者的临床资料，包括人口学指标、结直肠癌病情、手术资料及术后肠内营养相关情况等。采用多因素logistic回归分析筛选影响结直肠癌术后肠内营养不耐受的因素，根据筛选出的相关因素构建列线图预测模型，采用ROC曲线及校准曲线对模型的区分度和校准度进行验证。结果年龄大、有营养风险、术后卧床时间≥3 d、肠内营养开始时间≥48 h及使用镇痛类药物均为结直肠癌术后肠内营养不耐受的危险因素，添加膳食纤维是肠内营养不耐受的保护因素。基于各项影响因素构建列线图预测模型，经验证，模型C指数为0.808，一致性较好；校准曲线显示该模型具有较好的准确性。列线图模型预测结直肠癌术后肠内营养不耐受的ROC曲线下面积为0.823（95% CI：0.760~0.885），该模型具有良好的区分度。结论基于年龄、营养风险等影响因素构建的列线图预测模型具有良好的区分度和一致性，可作为临床预测结直肠癌患者术后肠内营养不耐受的有效工具。
- 结直肠癌 /
- 手术 /
- 肠内营养 /
- 不耐受 /
- 列线图
Abstract: Objective To develop a nomogram for predicting the risk of enteral nutrition intolerance after colorectal cancer surgery and to preliminarily validate the predictive performance. Methods A retrospective analysis was conducted on 185 colorectal cancer patients who underwent surgical treatment at the General Hospital of Eastern Theater Command from January 2021 to June 2024. All patients received postoperative enteral nutrition support. Based on the presence of intolerance symptoms, patients were divided into the tolerance group (n=129) and the intolerance group (n=56). The clinical data of the two groups were collected, including demographic indicators, colorectal cancer conditions, surgical data, and postoperative enteral nutrition-related conditions. Multivariate logistic regression analysis was used to identify the influencing factors for postoperative enteral nutrition intolerance. A nomogram prediction model was then constructed based on these factors. The discrimination and calibration of the model were verified by the receiver operating characteristic (ROC) curve and calibration curve. Results Advanced age, presence of nutritional risk, postoperative bed rest time ≥ 3 days, initiation of enteral nutrition ≥ 48 hours, and use of analgesic drugs were identified as risk factors for postoperative enteral nutrition intolerance, while dietary fiber supplementation was a protective factor. A nomogram model incorporating these variables was developed. The model demonstrated good discrimination, with a C-index of 0.808. The calibration curves showed good agreement between predicted and observed outcomes. The AUC for the nomogram predicting postoperative enteral nutrition intolerance in colorectal cancer was 0.823 (95% CI: 0.760-0.885), indicating satisfactory predictive efficacy. Conclusion The nomogram prediction model constructed based on influencing factors such as age and nutritional risk demonstrates good discrimination and consistency, and can serve as an effective tool for predicting postoperative enteral nutrition intolerance in colorectal cancer patients.
- Colorectal cancer /
- Surgery /
- Enteral nutrition /
- Intolerance /
- Nomogram

HTML全文

图 1 结直肠癌术后肠内营养不耐受的列线图预测模型

Figure 1. Nomogram prediction model for enteral nutrition intolerance after colorectal cancer surgery

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图 2 列线图预测模型的校准曲线

Figure 2. Calibration curve of the nomogram prediction model

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图 3 列线图模型预测结直肠癌术后肠内营养不耐受的ROC曲线

Figure 3. ROC curve analysis of the nomogram prediction model for enteral nutrition intolerance after colorectal cancer surgery

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表 1 结直肠癌术后肠内营养不耐受的单因素分析

Table 1. Univariate analysis of enteral nutrition intolerance after colorectal cancer surgery

项目	耐受组(n=129)	不耐受组(n=56)	统计量	P值
性别[例(%)]			0.016^a	0.900
男性	75(58.14)	32(57.14)
女性	54(41.86)	24(42.86)
年龄[M(P₂₅，P₇₅), 岁]	60.0(53.0, 65.0)	66.5(60.0, 73.0)	4.949^b	＜0.001
营养风险[例(%)]			5.970^a	0.015
有	11(8.53)	12(21.43)
无	118(91.47)	44(78.57)
肿瘤部位[例(%)]			0.057^a	0.811
结肠	83(64.34)	35(62.50)
直肠	46(35.66)	21(37.50)
肿瘤直径[M(P₂₅，P₇₅), cm]	3.2(2.3, 4.8)	3.7(2.5, 4.9)	1.042^b	0.298
肿瘤分化程度[例(%)]			0.258^b	0.796
低分化	61(47.29)	26(46.43)
中分化	35(27.13)	14(25.00)
高分化	33(25.58)	16(28.57)
TNM分期[例(%)]			0.136^a	0.713
Ⅰ~Ⅱ	82(63.57)	34(60.71)
Ⅲ~Ⅳ	47(36.43)	22(39.29)
淋巴结转移[例(%)]			0.002^a	0.961
是	35(27.13)	15(26.79)
否	94(72.87)	41(73.21)
手术方式[例(%)]			0.015^a	0.903
腹腔镜手术	91(70.54)	40(71.43)
开腹手术	38(29.46)	16(29.57)
手术时间[M(P₂₅，P₇₅), min]	159.00(132.00, 186.00)	165.00(149.25, 188.00)	1.604^b	0.109
平均动脉压[M(P₂₅，P₇₅), mmHg]	96.0(88.0, 104.0)	94.5(87.0, 102.0)	1.192^b	0.233
术后卧床时间[例(%)]			4.805^a	0.028
＜3 d	71(55.04)	21(37.50)
≥3 d	58(44.96)	35(62.50)
肠内营养方式[例(%)]			0.212^a	0.899
经口	45(34.88)	21(37.50)
鼻饲置管	60(46.51)	24(42.86)
造瘘	24(18.60)	11(19.64)
肠内营养开始时间[例(%)]			4.942^a	0.026
＜48 h	69(53.49)	20(35.71)
≥48 h	60(46.51)	36(64.29)
肠内营养配方[例(%)]			0.038^a	0.846
整蛋白型	81(62.79)	36(64.29)
短肽型或氨基酸型	48(37.21)	20(35.71)
添加膳食纤维[例(%)]			8.742^a	0.003
有	81(62.79)	22(39.29)
无	48(37.21)	34(60.71)
添加益生菌[例(%)]			0.050^a	0.822
有	53(41.09)	24(42.86)
无	76(58.91)	32(57.14)
使用抗菌药物种类[例(%)]			0.213^a	0.644
1种	83(64.34)	38(67.86)
≥2种	46(35.66)	18(32.14)
使用促胃动力药物[例(%)]			0.070^a	0.791
是	58(44.96)	24(42.86)
否	71(55.04)	32(57.14)
使用镇痛类药物[例(%)]			8.165^a	0.004
是	25(19.38)	22(39.29)
否	104(80.62)	34(60.71)
注：^a为χ²值，^b为Z值；1 mmHg=0.133 kPa。

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表 2 变量赋值情况

Table 2. The assignment situation of independent variables

变量	赋值方法
年龄	连续型变量，以实际值赋值
营养风险	无=0，有=1
术后卧床时间	＜3 d=0，≥3 d=1
肠内营养开始时间	＜48 h=0，≥48 h=1
添加膳食纤维	无=0，有=1
使用镇痛类药物	否=0，是=1

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表 3 结直肠癌术后肠内营养不耐受的多因素logistic回归分析

Table 3. Multivariate logistic regression analysis of postoperative enteral nutrition intolerance after colorectal cancer surgery

变量	B	SE	Waldχ²	P值	OR值	95% CI
年龄	0.130	0.028	21.540	＜0.001	1.139	1.078~1.203
有营养风险	1.177	0.536	4.824	0.028	3.245	1.135~9.275
术后卧床时间≥3 d	1.014	0.394	6.617	0.010	2.755	1.273~5.964
肠内营养开始时间≥48 h	0.753	0.333	5.113	0.024	2.123	1.106~4.077
添加膳食纤维	-0.881	0.379	5.396	0.020	0.414	0.197~0.871
使用镇痛类药物	0.990	0.353	7.877	0.005	2.692	1.348~5.375

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